SCHECHTER.HAGIT@GMAIL.COM
I am an AI researcher working at the intersection of 3D modeling, computer vision, anomaly detection, time-series analysis, and genomics. My work combines rigorous computational modeling with modern AI to design intelligent systems grounded in strong theoretical foundations.
I focus on bridging fundamental research and real-world impact, translating interdisciplinary insights into practical AI systems and innovation-oriented applications. My research connects theory, data, and deployment across simulation, perception, and applied AI.
I received my PhD from the University of British Columbia, Canada, where my research focused on particle methods for fluid simulation in computer graphics.
This site presents selected publications and research projects.
Publications
M. Serry, D. Danon, H. Schechter, and A. H. Bermano: Explainable 3D Reconstruction Using Deep Geometric Prior,
Microsoft Journal of Applied Research 2021. [ PDF ]
Technical Reports
H. Schechter and R. Bridson: The Beta Mesh, a New Approach for Temporally Coherent Particle Skinning, 2013 [ PDF ]
PhD Thesis
H. Schechter:
Enhancing Particle Methods for Fluid Simulation in Computer Graphics, The University of British Columbia, 2013. [ PDF ]